code: def test_model_label_encoder_str(self):
      model = LabelEncoder()
      data = [
          "paris",
          "tokyo",
          "amsterdam",
          "tokyo",
      ]
      model.fit(data)
  
      torch_model = hummingbird.ml.convert(model, "torch")
  
      np.testing.assert_allclose(
          model.transform(data),
          torch_model.transform(data),
          rtol=1e-06,
          atol=1e-06,
      )
  
file_path: hummingbird/tests/test_sklearn_label_encoder_converter.py
imports: import unittest
  import numpy
  import torch
  from sklearn.preprocessing import LabelEncoder
  import hummingbird.ml
  from onnxconverter_common.data_types import Int32TensorType
label_desc: Use image node_id 2 for calling the TestSklearnLabelEncoderConverter obj's underlying member method code with example usage: obj.test_model_label_encoder_str() without return types